Submission

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
df = df[df['year'] == 2007]
fig = px.histogram(df, 
                   x = 'pop', 
                   y = 'continent', 
                   color = 'continent', 
                   category_orders={"continent": ["Africa", "Americas", "Asia", "Europe", "Oceania"]}, 
                                     )
fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()

Question 2:

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
fig = px.histogram(df, 
                   x = 'pop', 
                   y = 'continent', 
                   color = 'continent', 
                   category_orders={"continent": ["Asia", "Americas", "Africa", "Europe", "Oceania"]}, 
                                     )
fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()

Question 3:

Add text to each bar that represents the population

In [5]:
fig = px.histogram(df, 
                   x = 'pop', 
                   y = 'continent', 
                   color = 'continent', 
                   category_orders={"continent": ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, 
                   text_auto = '.2s'
                  )
fig.update_traces(textposition = 'outside')
fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()

Question 4:

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [34]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", 
                   y="continent", 
                   animation_frame="year", 
                   animation_group="continent",
                   color="continent", 
                   range_x=[0,4000000000], 
                  ).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()

Question 5:

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [12]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", 
                   y="country", 
                   animation_frame="year", 
                   animation_group="country",
                   #size="pop", 
                   color="country", 
                   hover_name="country",
                   range_x=[0,4000000000], 
                  ).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()

Question 6:

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [16]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", 
                   y="country", 
                   animation_frame="year", 
                   animation_group="country",
                   #size="pop", 
                   color="country", 
                   hover_name="country",
                   range_x=[0,4000000000], 
                  ).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False, autosize = False, width=500, height=1000)
fig.show()

Question 7:

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [50]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", 
                   y="country", 
                   animation_frame="year", 
                   animation_group="country",
                   #size="pop", 
                   color="country", 
                   hover_name="country",
                   range_x=[0,2000000000], 
                   range_y = [132, 142]
                  ).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False)
fig.show()
In [46]:
 

142
In [ ]: